Evidence map›Paper›PMID 39779852›Full record

ArticleNature2025

A foundation model of transcription across human cell types.

Xi Fu, Shentong Mo, Alejandro Buendia, Anouchka P Laurent, Anqi Shao, Maria Del Mar Alvarez-Torres, Tianji Yu, Jimin Tan, Jiayu Su, Romella Sagatelian and 7 more

Abstract read
In one paragraph

Article in Nature, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

68 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Artificial intelligence virtual bone organoids (AIVBOs).Journal of orthopaedic translation · 2026
    Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Computational modelling of cell identity.The Biochemical journal · 2026
    Review
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

8 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Xi Fu *Program of Mathematical Genomics, Department of Systems Biology, Columbia University, New York, NY, USA. xf2217@cumc.columbia.edu.
Shentong Mo *Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE.
Alejandro Buendia *Program of Mathematical Genomics, Department of Systems Biology, Columbia University, New York, NY, USA.ORCID 0009-0001-6562-9876
Anouchka P LaurentInstitute for Cancer Genetics, Columbia University, New York, NY, USA.ORCID 0000-0001-7726-4723
Anqi ShaoDepartment of Dermatology, Columbia University, New York, NY, USA.
Maria Del Mar Alvarez-TorresProgram of Mathematical Genomics, Department of Systems Biology, Columbia University, New York, NY, USA.
Tianji YuProgram of Mathematical Genomics, Department of Systems Biology, Columbia University, New York, NY, USA.
Jimin TanInstitute for Systems Genetics, New York University Grossman School of Medicine, New York, NY, USA.
Jiayu SuProgram of Mathematical Genomics, Department of Systems Biology, Columbia University, New York, NY, USA.
Romella SagatelianProgram of Mathematical Genomics, Department of Systems Biology, Columbia University, New York, NY, USA.
Adolfo A FerrandoInstitute for Cancer Genetics, Columbia University, New York, NY, USA.
Alberto CicciaDepartment of Genetics and Development, Columbia University, New York, NY, USA.ORCID 0000-0003-4789-6564
Yanyan LanInstitute for AI Industry Research, Tsinghua University, Beijing, China.
David M OwensDepartment of Dermatology, Columbia University, New York, NY, USA.ORCID 0000-0003-0297-4370
Teresa PalomeroInstitute for Cancer Genetics, Columbia University, New York, NY, USA.
Eric P XingMohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE. epxing@cs.cmu.edu.
Raul RabadanProgram of Mathematical Genomics, Department of Systems Biology, Columbia University, New York, NY, USA. rr2579@cumc.columbia.edu.ORCID 0000-0001-7946-9255

Funding

Tumor Biology and Microenvironment ProgramP30CA013696 · NCI · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI Anil K Rustgi · 1985 to 2026
$115.3M
POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
The Role of CTIP in Lymphocyte Development and LymphomagenesisP01CA174653 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GAUTIER, JEAN · 2014 to 2024
$17.6M
Towards a quantitative understanding of tumor evolutionR35CA253126 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Raul Rabadan · 2021 to 2026
$5.6M
Single-cell characterization of tumor and microenvironment co-evolution in Peripheral T-cell LymphomasU01CA243073 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PALOMERO, TERESA, RABADAN, RAUL · 2019 to 2023
$3.0M
Investigating the role for Utrophin in age-related decline of the Merkel lineageR01AG073874 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI OWENS, DAVID MICHAEL · 2021 to 2025
$2.0M
NCI NIH HHS P01 CA174653NCI NIH HHS P30 CA013696NCI NIH HHS R35 CA253126NCI NIH HHS U01 CA243073NIA NIH HHS R01 AG073874NLM NIH HHS T15 LM007033
6 · The paper itself

Abstract

Transcriptional regulation, which involves a complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate to unseen cell types and conditions. Here we introduce GET (general expression transformer), an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types

Indexed as

Gene Expression RegulationModels, GeneticTranscription, GeneticAdultChromatinFetusGene Regulatory NetworksHumansOrgan SpecificityTranscription FactorsChromatinTranscription Factors

Identifiers

PMID39779852
PMCPMC11754112

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.